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dc.contributor.authorKaragrigoriou, Alexen
dc.contributor.authorMakrides, Andreasen
dc.contributor.authorTsapanos, T.en
dc.contributor.authorVougiouka, G.en
dc.creatorKaragrigoriou, Alexen
dc.creatorMakrides, Andreasen
dc.creatorTsapanos, T.en
dc.creatorVougiouka, G.en
dc.date.accessioned2019-12-02T10:36:15Z
dc.date.available2019-12-02T10:36:15Z
dc.date.issued2016
dc.identifier.issn1387-5841
dc.identifier.urihttp://gnosis.library.ucy.ac.cy/handle/7/57100
dc.description.abstractThis paper deals with earthquake long term predictions based on multi-state system methodology. As a reference we consider the South America case which was examined (Tsapanos, Bull Geol Soc Gr XXXIV/4:1611–1617, 2001) in the light of the Markov model, in order to define large earthquake recurrences. In this work we make the first attempt to describe seismic zoning data as data of a multi-state system (MSS) and explore earthquake genesis by evaluating intensity rates and transition probabilities between zones using various probabilistic models. For this purpose we incorporate into the procedure discussed in Tsapanos (2001) the effect, via the underlying distribution, of sojourn times between transitions. © 2015, Springer Science+Business Media New York.en
dc.sourceMethodology and Computing in Applied Probabilityen
dc.source.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-84930363614&doi=10.1007%2fs11009-015-9451-x&partnerID=40&md5=434e87573a0434a986f848fb2371f958
dc.subjectTransition probabilitiesen
dc.subjectMulti-state systemen
dc.subjectReliability theoryen
dc.subjectWeibull distributionen
dc.subjectEarthquake genesisen
dc.subjectEarthquake predictionsen
dc.subjectSeismic zonesen
dc.subjectTransition intensitiesen
dc.titleEarthquake Forecasting Based on Multi-State System Methodologyen
dc.typeinfo:eu-repo/semantics/article
dc.identifier.doi10.1007/s11009-015-9451-x
dc.description.volume18
dc.description.issue2
dc.description.startingpage547
dc.description.endingpage561
dc.author.facultyΣχολή Θετικών και Εφαρμοσμένων Επιστημών / Faculty of Pure and Applied Sciences
dc.author.departmentΤμήμα Μαθηματικών και Στατιστικής / Department of Mathematics and Statistics
dc.type.uhtypeArticleen
dc.description.notes<p>Cited By :1</p>en
dc.source.abbreviationMethodol.Comput.Appl.Probab.en
dc.contributor.orcidKaragrigoriou, Alex [0000-0002-4919-2133]
dc.gnosis.orcid0000-0002-4919-2133


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